After a goal space is determined, we need a sampling strategy to set next goals. Generally, desired next goals should be novel/diverse enough or lie on the boarder of the agent's knowledge boundary. Example strategies to select next goals include novelty [1]}, [2]}, learning progress [3]}, [4]}, diversity [5]}, [6]}, and uniform sampling [7]}. In this work, we use novelty (count-based) for sampling, since it has less tuneable hyper-parameters.
